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The terms "Data Science" and "Data Scientist" have only been in common usage for a little over a year, but they've really taken off since then: many companies are now hiring for "data scientists", and entire conferences are run under the name of "data science".

Heads-up to anyone attending the sold-out Data Science Summit in Las Vegas this week: I'll be there tomorrow and Thursday for the conference and to discuss R on the panel discussion "Data Science Toolset - Recipes That Win" (more details about the panel discussion below.) I'm looking forward to meeting with the other R users there --

The Rmetrics Association is once again holding its annual Workshop and Summer School on Computational Finance and Financial Engineering at Meielisalp (on Lake Thune in Switzerland) from June 26-30. Now in its fifth year, the workshop consists of Summer School-like tutorial sessions and a user/developer meeting:

As an Australian who lived in the UK for a long time and now lives in the US, it do find it funny when Americans talk about England (when referring to the entire UK), or who are surprised when they learn that the Queen is still my official Head of State. But let's face it, the whole British Empire thing is pretty confusing, especially when it comes to naming. I confess I learned a few things in the video below -- and the Venn diagram at the end is the best explanation of the whole shebang I've ever seen. (If you're in a rush, there's a screencap of the diagram after the jump.)

SocialFlow's blog has a great case study today on how news from a single tweet -- in this case, speculation made an hour before the President's announcement that Osama bin Laden had been killed -- can propagate through social networks.

Steve Miller tackles this topic in a 2-part series at Information Management. Part 1 is a great overview of Data Science, drawing on data science thought leaders including Mike Driscoll, Drew Conway, David Champagne and Nathan Yau.

From his presentation at the Greater Boston useR Group[*], R user Jeffrey Breen has shared some useful slides detailing how to bring data from relational databases like MySQL and Oracle.

Inspired by the Facebook Social Network chart, FlowingData's Nathan Yau also turns to R to create a beautiful chart of the network of all flight connections between major airlines in the US:

Data Scientist Antonio Piccolboni recently published this comparison of the various language and interfaces available for programming Big Data analysis tasks in the map-reduce framework. The interfaces he reviewed included:

Over at R community site inside-R.org, Revolution's Joseph Rickert has published a How-To guide with tips for new users on How to Learn R, with links to resources for R books, blogs and courses. Check it out at the link below.

Inside-R: How to Learn R